PreprintCited by 319Corporate Social Responsibility ReportingFinancial Markets and Investment StrategiesSustainable Finance and Green Bonds

Corporate ESG Profiles and Investor Horizons

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Starks, Laura T., Venkat, Parth, Zhu, Qifei·2017·The Journal of Finance

Abstract

We find that long-term institutional investors tilt their portfolios towards firms with better ESG profiles, in the cross-sections of both institutional investor portfolios and the ownership of firms. We test whether several theoretically motivated mechanisms can explain this relationship. Our results that long-term investors exhibit patience with firms around poor earnings announcements, but quickly sell portfolio firms after negative ES incidents, support the hypothesis that long term and short term investors evaluate information differently. In addition, our evidence shows that limits-to-arbitrage plays a role as we find investors’ ESG tilting weakens following regulatory shocks that shorten their horizon.

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Authors
Starks, L. T., Venkat, P., & Zhu, Q.
Venue
The Journal of Finance
Publisher
Elsevier BV
Published
2017
Volume
81
Issue
2
Pages
603-642
ISSN
0022-1082 (ISSN-L)
OpenAlex
W7118678074
Cited by
319
References
63
Citations by year
2026: 36 · 2025: 36 · 2024: 65 · 2023: 46 · 2022: 48 · 2021: 38 · 2020: 23 · 2019: 15 · 2018: 9 · 2017: 3
FWCI
212.54
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • The Journal of Finance (publishedVersion, cc-by-nc-nd)
  • SSRN Electronic Journal (acceptedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Corporate Social Responsibility Reporting
  • Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
  • Social Sciences › Economics, Econometrics and Finance › Finance › Sustainable Finance and Green Bonds
Keywords
long-term institutional investors, investment horizon, limits to arbitrage, earnings announcements, ESG incidents, regulatory shocks, ownership structure, portfolio optimization

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